Spatio-temporal variability of chlorophyll in the northern Indian Ocean: A biogeochemical argo data perspective

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Abstract

The Arabian Sea (AS) and the Bay of Bengal (BoB) form an integral part of the northern Indian Ocean, exhibiting distinct characteristics despite being in the same latitudinal region. The present study is aimed at assessing the surface and sub-surface chlorophyll-a (chl-a) structure of the AS and the BoB utilizing concurrent Biogeochemical-Argo measurements. As the calibration coefficients require post-processing evaluation to suit the regional waters, where the floats are deployed, two floats each in the AS (WMO ID: 2902093 & 2902118) and the BoB (WMO ID: 2902086 and 2902114) falling in the same latitudinal belt are chosen on a pilot basis for correcting the gain and offset of the derived chl-a. The chl-a derived using scale factor and dark counts provided by the manufacturer is further calibrated using satellite measured chlorophyll and modified chl-a values are obtained. The modified chl-a data obtained by applying the gain and offset was then used to study the variability of chlorophyll, deep chlorophyll maximum (DCM) and factors responsible for its variability in both basins. The present study upheld the existence of a permanent DCM in both the basins. Similarly, the relationship between DCM and mixed layer depth (MLD) is assessed and the DCM is found to vary at an annual mode in BoB and at a quasi-semi annual mode in the AS region. Strong correlation between DCM and depth of 26 °C isotherm was also observed in both AS and BoB and the rationale behind it was analyzed. Existence of sub-surface blooms in the pre-monsoon season in the upper 200 m of the AS region is observed. The time-series data from BGC-Argo floats revealed the bio-optical mechanisms and their relationship with the physical processes.

Introduction

Chlorophyll-a concentration (chl-a) in the upper water column is one of the key parameters to understand ocean biogeochemistry. Physical processes prevalent in the upper ocean not only regulate the vertical distribution of phytoplankton but also help to understand the underlying bloom dynamics. Availability of sunlight in the upper water column and nutrients (Boss et al., 2008) are the two major factors that govern the vertical distribution of chl-a. In the tropical waters such as the northern Indian Ocean, the chl-a is generally higher below the mixed layer, defined as deep chlorophyll maximum (DCM), and it is located at the base of the euphotic layer, generally between 50 and 200 m (Mignot et al., 2014). DCM often persists at the depths where optimal amounts of nutrients and light are available (Wang et al., 2009; Li et al., 2012).

The tropical Indian Ocean encompassing the Bay of Bengal (BoB) on the east and the Arabian Sea (AS) on the west is a landlocked basin that is influenced by the seasonally reversing monsoon system. During the summer monsoon (June–September), winds are stronger than during the winter monsoon (November–February) over both these basins. Accordingly, the surface circulation of these two basins undergo seasonal reversal between the two monsoons. The AS is productive during both the monsoon seasons though the governing mechanisms differ. During the summer monsoon season, upwelling occurring along the coasts of Somalia, Oman and the southwest coast of India due to the low-level wind jet blowing from the African coast to Gujarat in India, induces productivity within the region. Advection of these upwelled nutrients along with the positive wind stress curl and associated mixing and Ekman pumping lead to productivity in the central AS (Prasanna Kumar et al., 2009; Joseph et al., 2019). From these studies it was inferred that the total columnar integrated chl-a biomass is ~39.62 mg m-3 during the summer monsoon. During the winter monsoon season, dry continental winds blowing from northeasterly direction accompanied by reduction in the incoming solar radiation enhance the evaporation thereby cooling the northern AS. This cooling of surface waters triggers the convective mixing due to strong negative buoyancy flux results in the deepening of mixed layer depth (MLD) and entrains the nutrients towards the surface thus turning the northern AS more productive with integrated chlorophyll values up to ~24 mg m-3 (Madhupratap et al., 1996; Udaya Bhaskar et al., 2007; Prasanna Kumar et al., 2009). Biological productivity in the BoB is relatively less compared to the AS despite the heavy influx of nutrients through numerous rivers draining into the basin. Large freshwater flux, together with the enhanced precipitation, during the summer monsoon leads to a lower surface salinity thereby resulting in a strong density stratification within the surface layers. Relatively weaker winds over the BoB restrict the turbulent mixing to a shallow depth, ensuing in shallower MLD. These conditions leads to the formation of barrier layer, a layer between the bottom of mixed layer and the top of the thermocline that inhibits the transfer of subsurface nutrients towards the euphotic zone resulting in lesser productivity in the surface waters of BoB (Muraleedharan et al., 2007; Prasanna Kumar et al., 2004, 2009; Sarma et al., 2016). Irrespective of the season, the oligotrophic conditions and weak vertical mixing in the BoB are countered by eddy pumping and wind driven mixing due to tropical cyclone events. These factors are responsible for eroding the surface stratification; paving way for the entrainment of nutrients into the surface water thereby increasing the biological production (Singh and Ramesh, 2015; Sarma et al., 2018). Despite the existence of subsurface eddies, the productivity during the summer monsoon in BoB is less due to light limitation (Prasanna Kumar et al., 2010). Another typical feature of the BoB is the manifestation of DCM during all the seasons between 50 – 80 m of depth. This DCM is found to shoal during the summer monsoon but never reaches the surface owing to the stratified waters.

Many studies on chl-a variability were undertaken in the past using remote sensing data and limited in-situ data sets. Remote sensing is an important tool that provides information on distribution of surface chl-a at higher temporal and spatial scales. Remote sensing data has immensely helped to understand the seasonal evolution of productivity and its interannual variability, but lack of information on the DCM has been a major limitation and has often led to gross under-estimation of ocean productivity. Though many studies were undertaken extensively using remote sensing and in situ data sets, lack of systematic and concurrent measurements in both the AS and BoB did not allow in unraveling the exact reasons for the difference in productivity in these two basins. The only possible way to obtain information on the subsurface distribution of chl-a is to enhance in-situ data collection. Biogeochemical-Argo floats that are mounted with sensors such as chl-a and dissolved oxygen have filled this gap and have helped to provide information on the subsurface distribution of chl-a. It is, therefore, the need of the hour to have continuous (both in space and time) in-situ bio-optical measurements to decipher the evolution of DCM and to blend them with the remote sensing data to obtain a realistic understanding of ocean biogeochemistry (Xing et al., 2014).

The deployment of biogeochemical Argo (BGC-Argo) floats equipped with bio-optical sensors in addition to the traditional conductivity, temperature and density (CTD) has provided newer opportunities to automatically measure and archive long-term records of bio-optical properties of the oceans at a higher vertical (~1 m) and temporal (5–10 days) resolution (Xing et al., 2014; Mignot et al., 2014; Bittig et al., 2019; Wong et al., 2020; and Johnson et al., 2019). The measurements obtained by these floats are also useful for substantiating the satellite ocean colour missions through validation of the derived products like chl-a, to carry out biogeochemical studies and to estimate particulate organic carbon in the oceans (IOCCG, 2011; Organelli et al., 2017).

Though the data from BGC-Argo floats is promising, a study by Roesler et al. (2017), suggested that there is an overestimation of chl-a data measured by BGC-Argo floats by a factor of two. However, in their extensive analysis done for the global oceans, profiles pertaining to the northern Indian Ocean were not included (see Fig. 3. From Roesler et al. (2017) while arriving at this estimate. Hence, the objective of this study is two folds: (1) to use in-situ data from BGC-Argo floats, correct them for their calibration coefficients and check the applicability of correction factor suggested by Roesler et al. (2017) and (ii) use the calibrated/corrected chl-a data from BGC-Argo floats to study the seasonal evolution of chl-a both in AS and BoB in conjunction with the factors responsible for their evolution. For this, we have arbitrarily picked two floats each representing AS and BoB falling within the same latitudinal belt, corrected the observed chl-a using the calibration coefficients obtained by following the method described in section 2 and then studied the chl-a variability. Once the proposed correction method is observed to be worthy, the same will be applied to all the floats deployed by India in the northern Indian Ocean producing a research quality data.

Section snippets

Satellite data

MODerate Resolution Imaging Spectroradiometer (MODIS) – Aqua derived surface chl-a data were downloaded from NASA ocean colour website (https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua/). The 4km x 4km and 8-day, level – 3 standard mapped products were used in the present study for comparison with BGC-Argo-derived chl-a data. Co-location of Argo profiles with satellite data is carried out by averaging chl-a in a 0.25° x 0.25° box with profile location at the centre, as suggested by Boss et al.

Results and discussion

Despite being generally used, chl-a is an imperfect indicator of the phytoplankton biomass (Barbieux et al., 2019). The particulate backscattering coefficient often acts as a proxy for abundance of particles and particulate organic carbon (POC) in the open-ocean (Stramski et al., 1999; Barbieux et al., 2019; Bellacicco et al., 2019). Coupling between chl-a and particulate backscattering (bbp700) reflect an actual increase in carbon biomass, while decoupling reflects photo-acclimation or change

Summary and conclusion

Chl-a is one of the vital biogeochemical parameters of the oceans. Satellite observations of chlorophyll in conjunction with sea surface temperature characterize environmental factors that affect fish habitat. Most of the existing knowledge regarding the influence of phytoplankton dynamics on the global ocean carbon cycle is gained from remote sensing and ship-based observations. Continuous measurement of sub-surface profiles of chl-a were obtained using BGC-Argo floats which gives incessant

Author statement

Chiranjivi Jayaram and T V S Udaya Bhaskar worked with the raw data decoding, quality control and manuscript design. Neethu Chacko and KH Rao made contribution to the manuscript by including additional analysis. Satya Prakash helped in including discussion on factors responsible for biogeochemical parameter variability.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors sincerely thank GSFC - NASA are sincerely acknowledged for making available the level-3 chlorophyll data pertaining to MODIS-Aqua. BGC-Argo data provided by INCOIS as part of the international Argo project is gratefully acknowledged. These data were collected and made freely available by the International Argo Program and the national programs that contribute to it. (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System.

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